In this project, we seek to better understand the feedback processes among individuals and institutions that influence the effectiveness of public health policy toward infectious diseases at international borders. To study these processes, we will develop multilayer system models, which will parameterize socio-geo-economic features using various data sets. We have four Specific Aims: 1) To construct dynamic models of the US- Mexico border population measles immunization, transmission, and demography;2) to add computational descriptions of human behavior to our models and to study it's sensitivity to various perturbations;3) to identify relationships among institutional actors influencing immunization behavior, and incorporate institutions directly into our game-theory descriptions of human behavior and 4) to disseminate the model as opensource, publish the research results and analysis, and develop an online tutorial. From a practical perspective, this research will show how mobility patterns at international borders alter policy implementation, will help direct policy improvements, and will help inform public health practitioners. Through interactions with colleagues at Border Health a map of a complex community system will contribute to identifying the most parsimonious explanation of conditions for policy resistance and heuristic tools for policy development in contexts of high uncertainty and constant change. In terms of methodology, the system models developed will provide new analysis tools by combining preexisting tools with game theory, network analysis, and organizational analysis. PUBLIC HEALTH RELEVANCE: This research will help make sense of public health management of infectious diseases at the US-Mexico border. Scientifically, we will develop systems models of the interactions of people, infectious disease, and public policy to help us understand current public health problems. These models will be disseminated broadly for use in research and applications.